Environmental drivers of tree community turnover in western Amazonian forests

A more comprehensive understanding of the factors governing tropical tree community turnover at different spatial scales is needed to support land‐management and biodiversity conservation. We used new forest inventory data from 263 permanent plots in the Carnegie Biodiversity‐Biomass Forest Plot Network spanning the eastern Andes to the western Amazonian lowlands of Peru to examine environmental factors driving genus‐level canopy tree compositional variation at regional and landscape scales. Across the full plot network, constrained ordination analysis indicated that all environmental variables together explained 23.8% of the variation in community composition, while soil, topographic, and climatic variables each explained 15.2, 10.9, and 17.0%, respectively. A satellite‐derived metric of cloudiness was the single strongest predictor of community turnover, and constrained ordination revealed a primary gradient of environmentally‐driven community turnover spanning from cloudy, high elevation sites to warm, wet, lowland sites. For three focal landscapes within the region, local environmental variation explained 13.4–30.8% of compositional variation. Community turnover at the landscape scale was strongly driven by topo‐edaphic factors in the two lowland landscapes examined and strongly driven by potential insolation and topography in the montane landscape. At the regional scale, we found that the portion of compositional variation that was uniquely explained by spatial variation was relatively small (2.7%), and was effectively zero within the three focal landscapes. Overall, our results show strong canopy tree compositional turnover in response to environmental gradients at both regional and landscape scales, though the most important environmental drivers differed between scales and among landscapes. Our results also highlight the usefulness of key satellite‐derived environmental covariates that should be considered when conducting biodiversity analyses in tropical forests.     

The impact of regional landscape context on local maladaptive trait divergence: a field test using freshwater copepod acid tolerance

Theoretical work has shown that spatial landscape context can contribute to reducing local adaptation in populations depending on the spatial pattern of environmental heterogeneity, the spatial scale of distances between habitats on landscapes, and the level of habitat connectivity. However, only a handful of empirical studies have addressed the impact of regional landscape context on local trait divergence in natural populations. We tested if local adaptation in abiotic tolerance is diminished in landscapes with strong spatial heterogeneity and habitat proximity. We used a freshwater copepod (Leptodiaptomus minutus) that is known to show local adaptive divergence in acid tolerance as a study system to understand the effects of regional landscape-level spatial heterogeneity in lake/pond pH on local trait divergence. We compared local divergence in copepod acid tolerance from three types of landscapes: (i) a homogeneous pH landscape of exclusively circumneutral lakes (pH ≥ 6.0); (ii) a heterogeneous pH landscape with a mixture of acidic and circumneutral lakes; and (iii) a heterogeneous pH landscape in which relatively infrequent circumneutral ponds are embedded in a predominantly acidic landscape. We found that local adaptation to circumneutral lake/pond pH was most reduced in the pH-heterogeneous landscape dominated by acidic habitats, likely because of gene flow from surrounding nearby acidic ponds. Our study empirically confirms theoretical predictions that spatial landscape context is important for explaining regional differences in population environmental tolerances. These effects may become important for understanding regional differences in population fitness trade-offs when presented in combination with multiple stressors.     

Fine-scale analysis reveals cryptic landscape genetic structure in desert tortoises

Characterizing the effects of landscape features on genetic variation is essential for understanding how landscapes shape patterns of gene flow and spatial genetic structure of populations. Most landscape genetics studies have focused on patterns of gene flow at a regional scale. However, the genetic structure of populations at a local scale may be influenced by a unique suite of landscape variables that have little bearing on connectivity patterns observed at broader spatial scales. We investigated fine-scale spatial patterns of genetic variation and gene flow in relation to features of the landscape in desert tortoise (Gopherus agassizii), using 859 tortoises genotyped at 16 microsatellite loci with associated data on geographic location, sex, elevation, slope, and soil type, and spatial relationship to putative barriers (power lines, roads). We used spatially explicit and non-explicit Bayesian clustering algorithms to partition the sample into discrete clusters, and characterize the relationships between genetic distance and ecological variables to identify factors with the greatest influence on gene flow at a local scale. Desert tortoises exhibit weak genetic structure at a local scale, and we identified two subpopulations across the study area. Although genetic differentiation between the subpopulations was low, our landscape genetic analysis identified both natural (slope) and anthropogenic (roads) landscape variables that have significantly influenced gene flow within this local population. We show that desert tortoise movements at a local scale are influenced by features of the landscape, and that these features are different than those that influence gene flow at larger scales. Our findings are important for desert tortoise conservation and management, particularly in light of recent translocation efforts in the region. More generally, our results indicate that recent landscape changes can affect gene flow at a local scale and that their effects can be detected almost immediately.     

Avian taxonomic and functional diversity in early stage of longleaf pine (Pinus palustris) stands restored at agricultural lands: variations in scale dependency

In agricultural landscapes, the longleaf pine initiative (LLPI) and the Bobwhite Quail Initiative (BQI) aim to restore longleaf pine forests and early successional habitats, respectively. The early stage of longleaf pine stands and grass and forb vegetation produced by a combination of both restoration programs (LLPI‐BQI) may form habitat conditions favorable to early successional bird species and other birds, increasing avian diversity. We investigated how the LLPI and BQI programs affected taxonomic and functional diversity of birds and abundance of early successional birds (grassland and scrub/shrub species), and what environmental characteristics were associated with the diversity and abundance of birds. Our study was performed at 41 fields in Georgia, United States, during 2001–2002 by considering environmental characteristics at two spatial scales: local‐scale vegetation features and restoration program type (LLPI or LLPI‐BQI) and landscape‐scale vegetation features and landscape heterogeneity. Functional evenness, species richness, and abundance of grassland and scrub/shrub species did not show a clear association with local‐ or landscape‐scale variables. Shannon‐Wiener diversity was slightly influenced by restoration program type (local‐scale variable) with higher value at LLPI‐BQI stands than at LLPI stands despite no significant differences in local vegetation features between those stands. Functional divergence was strongly positively associated with landscape‐scale variables. That is, niche differentiation increased with increasing shrub coverage within a landscape, reducing competition between abundant bird species and others. Our results suggest that although a combination of BQI and LLPI program may have a positive effect on avian taxonomic diversity, it is important to consider shrub vegetation cover within a landscape to improve functional diversity.     

Scale‐dependent occupancy patterns in reptiles across topographically different landscapes

Understanding what factors influence species occupancy in human‐modified landscapes is a central theme in ecology. We examined scale‐dependent habitat relationships and site occupancy in reptiles across three topographically different study areas in south‐eastern Australia. We collected presence–absence data on reptiles from 443 sites associated with three long‐term biodiversity monitoring programs, on four to seven occasions, between 2001 and 2013. We characterised sites by the following four variable domains: 1) field design, 2) topography, 3) local‐scale vegetation attributes and 4) landscape‐scale vegetation cover. We constructed occupancy models for 14 species and used an information‐theoretic approach to compare multiple alternative hypotheses to explain occupancy within and between study areas. We modelled detection probability and used the model with the lowest AIC in subsequent analyses. We then modelled occupancy probability against all subsets of the variable groups (field design, topography, local‐ and landscape‐scale vegetation), as well as a model that held occupancy constant (null model). We found that local‐scale vegetation attributes were important for explaining site occupancy in 12/19 possible models, although, in several cases model fit was improved by the addition of topographic variables or native vegetation cover in the surrounding landscape. Occupancy models for widespread species were broadly congruent across study areas. We demonstrate that topographic variables are important for explaining reptile occupancy in hilly landscapes, and local‐ and landscape‐scale variables are important for explaining reptile occupancy in flat or gently undulating landscapes. Management actions that improve habitat complexity at a site‐level, and encompass entire topographic gradients, will have greater benefit to woodland reptiles than simply increasing vegetation cover in the surrounding landscape.     

Functional connectivity in replicated urban landscapes in the land snail (Cornu aspersum)

Urban areas are highly fragmented and thereby exert strong constraints on individual dispersal. Despite this, some species manage to persist in urban areas, such as the garden snail, Cornu aspersum, which is common in cityscapes despite its low mobility. Using landscape genetic approaches, we combined study area replication and multiscale analysis to determine how landscape composition, configuration and connectivity influence snail dispersal across urban areas. At the overall landscape scale, areas with a high percentage of roads decreased genetic differentiation between populations. At the population scale, genetic differentiation was positively linked with building surface, the proportion of borders where wooded patches and roads appeared side by side and the proportion of borders combining wooded patches and other impervious areas. Analyses based on pairwise genetic distances validated the isolation‐by‐distance and isolation‐by‐resistance models for this land snail, with an equal fit to least‐cost paths and circuit‐theory‐based models. Each of the 12 landscapes analysed separately yielded specific relations to environmental features, whereas analyses integrating all replicates highlighted general common effects. Our results suggest that urban transport infrastructures facilitate passive snail dispersal. At a local scale, corresponding to active dispersal, unfavourable habitats (wooded and impervious areas) isolate populations. This work upholds the use of replicated landscapes to increase the generalizability of landscape genetics results and shows how multiscale analyses provide insight into scale‐dependent processes.     

Natural regeneration as a tool for large‐scale forest restoration in the tropics: prospects and challenges

A major global effort to enable cost‐effective natural regeneration is needed to achieve ambitious forest and landscape restoration goals. Natural forest regeneration can potentially play a major role in large‐scale landscape restoration in tropical regions. Here, we focus on the conditions that favor natural regeneration within tropical forest landscapes. We illustrate cases where large‐scale natural regeneration followed forest clearing and non‐forest land use, and describe the social and ecological factors that drove these local forest transitions. The self‐organizing processes that create naturally regenerating forests and natural regeneration in planted forests promote local genetic adaptation, foster native species with known traditional uses, create spatial and temporal heterogeneity, and sustain local biodiversity and biotic interactions. These features confer greater ecosystem resilience in the face of future shocks and disturbances. We discuss economic, social, and legal issues that challenge natural regeneration in tropical landscapes. We conclude by suggesting ways to enable natural regeneration to become an effective tool for implementing large‐scale forest and landscape restoration. Major research and policy priorities include: identifying and modeling the ecological and economic conditions where natural regeneration is a viable and favorable land‐use option, developing monitoring protocols for natural regeneration that can be carried out by local communities, and developing enabling incentives, governance structures, and regulatory conditions that promote the stewardship of naturally regenerating forests. Aligning restoration goals and practices with natural regeneration can achieve the best possible outcome for achieving multiple social and environmental benefits at minimal cost.     

Modelling the occurrence of threatened plant species in taiga landscapes: methodological and ecological perspectives

Aim Understanding the spatial patterns of species distribution and predicting the occurrence of high biological diversity and rare species are central themes in biogeography and environmental conservation. The aim of this study was to model and scrutinize the relative contributions of climate, topography, geology and land‐cover factors to the distributions of threatened vascular plant species in taiga landscapes in northern Finland. Location North‐east Finland, northern Europe. Methods The study was performed using a data set of 28 plant species and environmental variables at a 25‐ha resolution. Four different stepwise selection algorithms [Akaike information criterion (AIC), Bayesian information criterion (BIC), adaptive backfitting, cross selection] with generalized additive models (GAMs) were fitted to identify the main environmental correlates for species occurrences. The accuracies of the distribution models were evaluated using fourfold cross‐validation based on the area under the curve (AUC) derived from receiver operating characteristic plots. The GAMs were tentatively extrapolated to the whole study area and species occurrence probability maps were produced using GIS techniques. The effect of spatial autocorrelation on the modelling results was also tested by including autocovariate terms in the GAMs. Results According to the AUC values, the model performance varied from fair to excellent. The AIC algorithm provided the highest mean performance (mean AUC = 0.889), whereas the lowest mean AUC (0.851) was obtained from BIC. Most of the variation in the distribution of threatened plant species was related to growing degree days, temperature of the coldest month, water balance, cover of mire and mean elevation. In general, climate was the most powerful explanatory variable group, followed by land cover, topography and geology. Inclusion of the autocovariate only slightly improved the performance of the models and had a minor effect on the importance of the environmental variables. Main conclusions The results confirm that the landscape‐scale distribution patterns of plant species can be modelled well on the basis of environmental parameters. A spatial grid system with several environmental variables derived from remote sensing and GIS data was found to produce useful data sets, which can be employed when predicting species distribution patterns over extensive areas. Landscape‐scale maps showing the predicted occurrences of individual or multiple threatened plant species may provide a useful basis for focusing field surveys and allocating conservation efforts.     

基于景观及微地形特征的丘陵区土壤属性预测

为探讨小流域尺度丘陵区的高分辨率数字土壤制图方法,通过对景观相分类的探索,配合应用不同尺度的Geomorphons(GM)微地形特征数据构成分类变量组参与高分辨率土壤pH、黏粒含量和阳离子交换量的预测制图,并与传统数字高程模型衍生变量和遥感变量进行组合与比较分析。此外,采用支持向量机、偏最小二乘回归和随机森林3种机器学习模型择优与残差回归克里金复合参与预测模型的构建与评价。结果表明: 景观及多尺度微地形分类变量组的应用分别提高小流域尺度丘陵地貌区pH、黏粒含量和阳离子交换量预测精度的18.8%、8.2%和8.7%。包含植被信息的景观相分类图相比土地利用数据有更高的模型贡献度;5 m分辨率的GM微地形分类图相比低分辨率的分类图更适宜高精度的预测制图。黏粒含量使用随机森林复合模型有最高的预测精度,而pH和阳离子交换量则不适宜在随机森林模型的基础上加入残差回归克里金模型。景观-多尺度微地形分类变量、数字高程模型衍生变量和遥感变量三者结合的模型预测表现最佳,表明多元变量在起伏地形区域相比单一数据源能够包含更多的土壤有效信息。由GM数据和地表景观数据组成的景观分类变量组作为主要变量能够解释小流域丘陵区部分土壤属性约40%的空间变异。在同类型土壤预测制图研究中,多分辨率GM及景观分类数据有潜力作为环境变量参与预测模型的构建。     

Biome transitions as centres of diversity: habitat heterogeneity and diversity patterns of West African bat assemblages across spatial scales

It is widely accepted that species diversity is contingent upon the spatial scale used to analyze patterns and processes. Recent studies using coarse sampling grains over large extents have contributed much to our understanding of factors driving global diversity patterns. This advance is largely unmatched on the level of local to landscape scales despite being critical for our understanding of functional relationships across spatial scales. In our study on West African bat assemblages we employed a spatially explicit and nested design covering local to regional scales. Specifically, we analyzed diversity patterns in two contrasting, largely undisturbed landscapes, comprising a rainforest area and a forest‐savanna mosaic in Ivory Coast, West Africa. We employed additive partitioning, rarefaction, and species richness estimation to show that bat diversity increased significantly with habitat heterogeneity on the landscape scale through the effects of beta diversity. Within the extent of our study areas, habitat type rather than geographic distance explained assemblage composition across spatial scales. Null models showed structure of functional groups to be partly filtered on local scales through the effects of vegetation density while on the landscape scale both assemblages represented random draws from regional species pools. We present a mixture model that combines the effects of habitat heterogeneity and complexity on species richness along a biome transect, predicting a unimodal rather than a monotonic relationship with environmental variables related to water. The bat assemblages of our study by far exceed previous figures of species richness in Africa, and refute the notion of low species richness of Afrotropical bat assemblages, which appears to be based largely on sampling biases. Biome transitions should receive increased attention in conservation strategies aiming at the maintenance of ecological and evolutionary processes.     

Multi-species richness of boreal agricultural landscapes: effects of climate, biotope, soil and geographical location

Aim To assess the relative importance of climate, biotope and soil variables as well as geographical location for the species richness of plants, butterflies, day‐active macromoths and wild bees in boreal agricultural landscapes. Location A total of 68 agricultural landscapes located in southern Finland. Methods Generalized linear mixed models were used to analyse the effects of environmental (climate, biotope and soil) and spatial (latitude and longitude) variables on species richness of four taxa in 136 study squares of 0.25 km². Using partial regression, the variation in species richness was decomposed into the purely environmental fraction; the spatially structured environmental fraction; and the purely spatial fraction, including variables retained in cubic trend surface regression. Results Species richness of all taxa was positively correlated with temperature. Species richness of plants and butterflies was also positively correlated with the heterogeneity of landscape. The extent of low‐intensity agricultural land and forest had a positive effect, and the extent of cultivated field a negative effect on the species richness of these taxa. The effect of soil characteristics on the number of observed species was negligible for all taxa. The greatest part of the explained variation for all taxa was accounted for by the pure effect of geographical location. To a somewhat lesser extent, the species richness of plants, butterflies and bees was also related to the effects of spatially structured environmental variables, and the species richness of macromoths to the effects of environmental variables. Main conclusions Multi‐species richness of boreal agricultural landscapes at the scale of 0.25 km² was associated with the heterogeneity of the local landscape. However, large‐scale geographical variation in species richness was also observed, which indicates the importance of climate and geographical location for the taxa studied. These results highlight the fact that, even on a landscape scale, geographical factors should be taken into account in biodiversity studies. Heterogeneous agricultural landscapes, including forest and non‐crop biotopes, should be preserved or restored to maintain biodiversity.     

Woody riparian plant distributions in western Oregon,USA: comparing landscape and local scale factors

We studied riparian forests along mountain streams in four large watersheds of western Oregon and far northern California, USA, to better understand the multiscale controls on woody riparian vegetation in a geographically complex region. In each of the four-study watersheds, we sampled woody riparian vegetation in161-ha sampling reaches that straddled the stream channel. Within each hectare, we sampled riparian vegetation and local environmental factors in 40 m² sampling plots arrayed along topographic transects. We also surveyed natural disturbance gaps in 6 ha in each watershed to explore the effects of fine scale disturbance on species distributions. We compared species composition across our study watersheds and used Nonmetric Multidimensional Scaling (NMS) and chi-squared analyses to compare the relative importance of landscape scale climate variables and local topographic and disturbance variables in explaining species distributions at sampling plot and hectare scales. We noted substantial turnover in the riparian flora across the region, with greatest numbers of unique species in watersheds at the ends of the regional gradient. In NMS ordinations at both scales, variation in woody riparian species composition showed strongest correlations with climatic variables and Rubus spectabilis cover, but the latter was only an important factor in the two northern watersheds. At the smaller scale, topographic variables were also important. Chi-squared analyses confirmed that more species showed landscape scale habitat preferences (watershed associations) than associations with topographic position (94.7% vs. 42.7% of species tested) or gap versus forest setting (94.7% vs. 24.6% of species tested). The woody riparian flora of western Oregon shows important biogeographic variation; species distributions showed strong associations with climatic variables, which were the primary correlates of compositional change between riparian sites at both scales analyzed. Additional local variation in composition was explained by measures of topography and disturbance.     

景观遗传学原理及其在生境片断化遗传效应研究中的应用

景观遗传学是近年来在景观生态学和种群遗传学之间形成的一个交叉领域,强调景观的组成、空间构型和环境梯度对基因流、种群遗传空间结构和局域种群适应的影响。景观遗传学尚未成为一门独立的学科,其理论基础主要来自分子遗传学、种群生物学和景观生态学。现代分子遗传标记技术、遥感和GIS支持下的景观分析和空间统计方法的综合运用是景观遗传学主要研究途径。系统介绍了景观遗传学的基础概念,关键科学问题,基本理论框架,及其与相邻研究领域的关系,综述了景观遗传学最为关注的现实课题——景观碎裂化的种群遗传效应的研究进展,主要涉及生境片断化的遗传效应、不同属性的物种响应、以及生境片断化过程的选择作用等方面。通过采取一种跨尺度的视角,景观遗传学研究显著深化了关于景观碎裂化对生物多样性影响的理解。     

Large Mammal Distribution in a Transfrontier Landscape: Trade‐offs Between Resource Availability and Human Disturbance

Understanding factors that affect the persistence of charismatic megafauna in human‐dominated landscapes is crucial to inform conservation decision‐making and reduce human‐wildlife conflict. We assessed the effect of environmental and anthropogenic factors at different landscape and management scales in predicting the distribution of African elephant (Loxodonta africana) within the Greater Mapungubwe Transfrontier Conservation Area in Southern Africa. We combined aerial distribution counts over a 12‐yr period with 14 variables, representing food availability, landscape, and anthropogenic effects, into generalized linear models. Generalized linear models were run for the broader landscape, as well as three separate management units within the broader landscape, namely ecotourism, trophy hunting, and a combination of hunting and ecotourism. Human activities within different management units forced elephant to trade‐off between disturbance avoidance, and good food and water availability. In addition, the important predictors of elephant distribution within each of the management units differed from the predictors at the broader landscape. Overall, our results suggest that at the fine scale, elephant are constraint by factors that may be masked at the broader landscape scale. We suggest that accounting for anthropogenic disturbance is important in determining the distribution of large, wide‐ranging, mammal species in increasingly human‐dominated landscapes, and that modeling needs to be done at the spatial scales at which conservation decisions are made.     

A global assessment of primate responses to landscape structure

Land‐use change modifies the spatial structure of terrestrial landscapes, potentially shaping the distribution, abundance and diversity of remaining species assemblages. Non‐human primates can be particularly vulnerable to landscape disturbances, but our understanding of this topic is far from complete. Here we reviewed all available studies on primates' responses to landscape structure. We found 34 studies of 71 primate species (24 genera and 10 families) that used a landscape approach. Most studies (82%) were from Neotropical forests, with howler monkeys being the most frequently studied taxon (56% of studies). All studies but one used a site‐landscape or a patch‐landscape study design, and frequently (34% of studies) measured landscape variables within a given radius from the edge of focal patches. Altogether, the 34 studies reported 188 responses to 17 landscape‐scale metrics. However, the majority of the studies (62%) quantified landscape predictors within a single spatial scale, potentially missing significant primate–landscape responses. To assess such responses accurately, landscape metrics need to be measured at the optimal scale, i.e. the spatial extent at which the primate–landscape relationship is strongest (so‐called ‘scale of effect’). Only 21% of studies calculated the scale of effect through multiscale approaches. Interestingly, the vast majority of studies that do not assess the scale of effect mainly reported null effects of landscape structure on primates, while most of the studies based on optimal scales found significant responses. These significant responses were primarily to landscape composition variables rather than landscape configuration variables. In particular, primates generally show positive responses to increasing forest cover, landscape quality indices and matrix permeability. By contrast, primates show weak responses to landscape configuration. In addition, half of the studies showing significant responses to landscape configuration metrics did not control for the effect of forest cover. As configuration metrics are often correlated with forest cover, this means that documented configuration effects may simply be driven by landscape‐scale forest loss. Our findings suggest that forest loss (not fragmentation) is a major threat to primates, and thus, preventing deforestation (e.g. through creation of reserves) and increasing forest cover through restoration is critically needed to mitigate the impact of land‐use change on our closest relatives. Increasing matrix functionality can also be critical, for instance by promoting anthropogenic land covers that are similar to primates' habitat.     

Continuum or discrete patch landscape models for savanna birds? Towards a pluralistic approach

Conceptualising landscapes as a mosaic of discrete habitat patches is fundamental to landscape ecology, metapopulation theory and conservation biology. An emerging question in ecology is: when is the discrete patch model more appropriate than alternative and conceptually appealing models such as the continuum model? There is limited empirical testing of the utility of alternative landscape models compared to the discrete patch model for a range of species. In this paper, we constructed three alternative sets of models for testing the effect of landscape structure on diversity and abundance of a suite of woodland birds in a savanna landscape of northern Australia: the null model (only site‐scale habitat variables, landscape context not important), the continuum model, and the discrete patch model. We utilised high‐spatial resolution satellite images to quantify spatial gradients in tree cover density (the continuum model), and to then aggregate the fine‐scale heterogeneity in tree cover into discrete patches of trees, with grass cover forming the “matrix” (the discrete patch‐model). We then evaluated the relative importance of the alternative models using generalised linear models and an information theoretic approach. We found that the importance of the models varied among species, with no single model dominant. Species that move between open grassy areas and woody shelter responded well to the continuum model, reflecting the importance of gradients in density of forage (grasses) and cover (trees), while the discrete model performed best for species that forage in all vegetation strata, and nest predominantly in dense woody vegetation. This finding supports a pluralistic approach, highlighting the need for adopting and testing more than one landscape model in savanna landscapes, and in other landscapes that do not have a well defined patch structure.     

Spatial Heterogeneity in Human Activities Favors the Persistence of Wolves in Agroecosystems

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people.     

An improved neutral landscape model for recreating real landscapes and generating landscape series for spatial ecological simulations

Many studies have assessed the effect of landscape patterns on spatial ecological processes by simulating these processes in computer‐generated landscapes with varying composition and configuration. To generate such landscapes, various neutral landscape models have been developed. However, the limited set of landscape‐level pattern variables included in these models is often inadequate to generate landscapes that reflect real landscapes. In order to achieve more flexibility and variability in the generated landscapes patterns, a more complete set of class‐ and patch‐level pattern variables should be implemented in these models. These enhancements have been implemented in Landscape Generator (LG), which is a software that uses optimization algorithms to generate landscapes that match user‐defined target values. Developed for participatory spatial planning at small scale, we enhanced the usability of LG and demonstrated how it can be used for larger scale ecological studies. First, we used LG to recreate landscape patterns from a real landscape (i.e., a mountainous region in Switzerland). Second, we generated landscape series with incrementally changing pattern variables, which could be used in ecological simulation studies. We found that LG was able to recreate landscape patterns that approximate those of real landscapes. Furthermore, we successfully generated landscape series that would not have been possible with traditional neutral landscape models. LG is a promising novel approach for generating neutral landscapes and enables testing of new hypotheses regarding the influence of landscape patterns on ecological processes. LG is freely available online.     

Lizard habitat partitioning on islands: the interaction of local and landscape scales

Aim This study addresses how species resolve environmental differences into biological habitats at multiple, interacting spatial scales. How do patterns of local habitat use change along an elevation gradient? How do patterns of local habitat partitioning interact with partitioning at a landscape scale? Location Northern and southern Lesser Antilles islands, West Indies. Methods We document how Anolis Daudin, 1802 lizards partition habitat locally at sites along a landscape‐scale elevation gradient. We examine habitat partitioning both with and without interspecific interactions in the predominately flat northern Lesser Antilles islands and in the more mountainous southern islands. Results Anoles partition local habitat along perch‐height and microclimate axes. Northern‐group sympatric anoles partition local habitat by perch height and have overlapping distributions at the landscape scale. Southern‐group sympatric anoles partition local habitat by microclimate and specialize in particular habitats at the landscape scale. In both the northern and southern groups, species use different perch heights and microclimates only in areas of species overlap along the elevation gradient. Main conclusions We demonstrate the interaction between local‐ and landscape‐scale habitat partitioning. In the case of microclimate partitioning, the interaction results from the use of thermal physiology to partition habitat at multiple scales. This interaction prompts the question of whether habitat partitioning developed ‘local‐out’ or ‘landscape‐in’. We pose this dichotomy and present a framework for its resolution.